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This section describes the basic methods of data in series and Dataframe Re-index An important method of Pandas objects is reindex, which is to create a new object that adapts to the new index" "Created on 2016-8-10@author:xuzhengzhu" "" "Created on 2016-8-10@author:xuzhengzhu" " fromPandasImport*Print "--------------obj Result:-----------------"o
Delete one or more columns of Pandas Dataframe:method One : Direct del df[' Column-name ']method Two : Using the Drop method, there are three types of equivalent expressions:1. df= df.drop (' column_name ', 1);2. Df.drop (' column_name ', Axis=1, Inplace=true)3. Df.drop ([df.columns[[0,1, 3]], axis=1,inplace=true) # Note:zero indexedNote : Usually there is a inplace optional parameter that modifies the original ar
The pandas Series is much more powerful than the numpy array , in many waysFirst, the pandas Series has some methods, such as:The describe method can give some analysis data of Series :Import= PD. Series ([1,2,3,4]) d = s.describe ()Print (d)Count 4.000000mean 2.500000std 1.290994min 1.00000025% 1.75000050% 2.50000075% 3.250000max
array ([[3, 4], [6, 7]) After understanding the step slice, the two-dimensional and three-dimensional aspects have the same good understanding, and are not as complicated as the step.You can also copy the sliced elements. >>> B [1:,: 2] = 1 # broadcast assignment >>> barray ([[0, 1, 2], [1, 1, 5], [1, 1, 8]) >>> B [1:,: 2]. shape (2L, 2L) >>> B [1:,: 2] = np. arange (2, 6 ). reshape () # corresponding value >>> barray ([[0, 1, 2], [2, 3, 5], [4, 5, 8
Tags: table name examples path Builder list defines an AC tin. sqlFirst we're going to create sparksession Val spark = Sparksession.builder () . AppName ("Test"). Master ("local") . Getorcreate () Import Spark.implicits._//Convert RDD into dataframe and support SQL operations Then we create
(Na.ctypes.data, ' \ n ', NA) 140269607002576 [6.93023941e-310 1.01768729e-316 0.00000000e+000] Second, using struct structure to realize dynamic structure arrayUsing the struct structure to receive the row, using ByteArray to store binary data, using Frombuffer to read data, which uses the need to pay attention to the data parsing format settings to conform to the struct receive format settingsImport structbuf = ByteArray () for I in range (5): buf + = Struct.pack (' =hdd
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